It is well known from studies of color perception that any color can be reproduced in a suitable display device as a combination of three primary colors. Thus, for purposes of image storage, transmission and display, it is convenient to represent the color of each pixel of a digitized image by specifying three coefficients, each representing the contribution from a respective primary color. Because human beings perceive a continuous range of colors, it would, in principle, require an infinite amount of information to specify any one particular color. That is, each of the three coefficients would be of unlimited length.
Such a representational system would of course be impractical. However, it has been found sufficient, for many purposes, to replace the continuous range of colors by a discrete set of colors. The specification of a discrete set of colors is referred to as “color quantization.” For example, a so-called full-color display system allocates eight bits to each of the three primary color coefficients. Therefore, each color in such a system is specified by a total of 24 bits, and the total number of specifiable colors is therefore 224, or about seventeen million separate colors.
In fact, there are many applications in which an even smaller selection of colors suffices. Thus, for example, a string of fewer than 24 bits, typically of only 8, 12, or 16 bits, represents each displayable color in most currently available display monitors. Here, we refer to each such string as a “symbol.”
Typically, some subset of available colors, referred to as the “color codebook,” is selected from the full color set. The selection may be the same for all images, in which case the color codebook is said to be “image independent.” Alternatively, the selection may be specially adapted for individual images or groups of images. In that case, the color codebook is said to be “image dependent.”
Each symbol serves as an index into the color codebook, for retrieving a corresponding color. Thus, a given symbol does not necessarily bear a direct relation to the three primary color coefficients that would be used in a display to reconstruct the corresponding color. Instead, the information necessary for reconstruction would be retrieved from stored information.
In fact, the symbols in many conventional color codebooks are randomly assigned and bear no correlation with the underlying colors. As a consequence, the digital processing of color information in conventional systems cannot take place directly at the symbolic level. Instead, each symbol must be converted to a point in a multidimensional color space for processing.
By contrast, the “color” values of gray-scale images fall along a single axis, i.e., a one-dimensional space. As a consequence, each pixel of such an image is readily assigned a symbol that relates directly to the quantized gray-scale value of that pixel. Simple and computationally fast algorithms are available for performing spatial filtering and other processing of gray-scale images that have been color-quantized in such a manner.
Until now, however, there has lacked any method for quantizing color images that affords similar advantages of simple and computationally fast image-processing algorithms that operate, at least partially, in the symbolic domain.